Today's oil and gas drilling operations often face significant technical challenges, especially in remote locations with increasingly difficult geological settings. Stuck pipe incidents have become a major operational challenge for the exploration and production industry, with events typically resulting in substantial amounts of lost time and associated costs. Real-time monitoring has emerged as an important tool to achieve drilling optimization in avoiding downtime, particularly stuck pipe incidents. With the addition of a predictive monitoring system, this process becomes much more effective and competent. Predictive monitoring is used for advanced real-time monitoring in Wells Real Time Center (WRTC) and operational workflows to aid in the drilling execution of complex or critical well sections. The emphasis will be on reducing the complexity of real-time data analysis by utilizing trends and deviations between modelled and actual data to monitor wellbore conditions. This monitoring system and trend-based predictive capability enable drilling teams to detect borehole changes and take preventive action up to several hours in advance. By maximizing productive time, it improves operational efficiency. Predictive monitoring can provide early warning of stuck pipe symptoms, allowing the rig and operations team to take corrective and step-by-step actions. In raw drilling data, the conditions that lead to the stuck pipe can be difficult to read and detect. Various factors may indicate potential problems, but these are frequently missed until the situation has progressed to the point where the drill string becomes stuck. This system could have provided the rig crew with advance notice of changes in downhole conditions, in this case, avoiding the stuck pipe situation. We will look into predictive monitoring adoption in Field B operation as an example. Well E is a highly deviated extended reach well (ERD), with a 12,000ft long horizontal section, exceptionally challenging in terms of geomechanics perspective as well as the well design. When original Well E was drilled, a stuck pipe was encountered which caused the wellbore to be sidetracked. Predictive monitoring was implemented to assist drilling operation for the sidetracked well, and it had been completed successfully with minor hole condition issues. The predictive monitoring system is built around a trio of tightly coupled real-time dynamic models consisting of hydraulic, mechanical, and thermodynamic that simulate the wellbore state and physical processes during drilling operations. These models work together continuously to assess drilling performance, borehole conditions, and any other associated risks. It uses dynamic modelling to accurately model key drilling parameters and variables such as hook load, surface torque, cuttings transport, tank volumes, standpipe pressure, and equivalent circulating density (ECD) in real-time.

Significant technical challenges are prominent in today's oil and gas drilling operations, especially in remote locations with increasingly difficult geological settings. Stuck pipe incidents have become a major operational challenge, with events typically resulting in substantial amounts of lost time and associated costs. Real-time monitoring has emerged as an important tool to achieve drilling optimization in avoiding downtime, particularly stuck pipe events. With the addition of a predictive monitoring system, this process becomes much more effective and competent. Predictive monitoring is used for advanced real-time monitoring in the remote centre and operational workflows to aid in the drilling execution of complex or critical well sections. The emphasis will be on reducing the complexity of real-time data analysis by exploiting trends and anomalies between modelled and actual data to monitor wellbore conditions. This monitoring system and trend-based predictive capability enable drilling teams to detect borehole changes and take preventive action up to several hours in advance. Predictive monitoring can provide early warning of stuck pipe symptoms, allowing the rig and operations team to take corrective and step-by-step actions. The circumstances that lead to the stuck pipe can be difficult to detect as various factors may indicate potential problems. These are frequently missed until the situation has progressed to the point where the drill string becomes stuck. This system could have provided the rig crew with advance notice of changes in downhole conditions. An example of predictive monitoring adoption in a highly deviated extended reach well (ERD), with a 12,000ft long horizontal section is presented. It is exceptionally challenging in terms of geomechanics perspective as well as the well design. Predictive monitoring was implemented to assist drilling operation for the sidetracked well, and it had been completed successfully with minor hole condition issues. The predictive monitoring system is built around a trio of tightly coupled real-time dynamic models consisting of hydraulic, mechanical, and thermodynamic that simulate the wellbore state and physical processes during drilling operations. These models work simultaneously in a seamless process to assess drilling performance, borehole conditions, and related associated risks. It uses dynamic modelling to accurately model key drilling parameters and variables, allowing better monitoring.